The present invention pertains to the field of digital printing and imaging, and is specifically directed to the reproduction of digitized documents.
With the growing use of digital input means such as digital scanners and cameras, and digital printers, users will demand more flexibility in their choice of input and output devices. Thus it becomes important to be able to repurpose documents and images automatically and efficiently. The term repurpose is defined as follows. Any multimedia object such as text, images, audio and video is created with a specific purpose in mind, i.e. a target audience and conditions under which the object is consumed by the audience. By repurposing, we mean processing the multimedia object so that it serves a different purpose, i.e a different target audience and conditions governing the use of the object. For instance, a newspaper agency would like to format text and images for printing in a newspaper, and take the same content and repurpose it for on-line viewing on the Web. If a better printer becomes available, a user will be interested in taking pictures scanned and formatted for an original printer and printing them on an improved printer. Since the original scanned document or object is invariably not available, it is crucial for this repurposing to be done automatically from the available halftone.
With the growing use of multimedia objects as well as the increasing number of choices for output media, such as different printers and monitors, it is very hard to anticipate all the uses of an object at the time of creation, and it is also difficult to repurpose the object as it may involve very complex processing steps.
An instance of this problem is to take a halftoned image prepared for one printer, and process it such that when it is halftoned and printed on a second printer, the outputs of the two printers are visually as similar as possible. This problem is known as xe2x80x9cdescreeningxe2x80x9d or xe2x80x9cinverse halftoningxe2x80x9d in the literature.
A bi-level composite document containing both text and image areas, is comprised of a collection of individual pixels, each of which has only two values. These values could be xe2x80x9c1xe2x80x9d or a xe2x80x9c0xe2x80x9d, with xe2x80x9c1xe2x80x9d signifying black, such as a printed dot, and xe2x80x9c0xe2x80x9d signifying white. Currently, there is no satisfactory solution to repurposing this document for another printer. Some of the obstacles in solving this problem are as follows:
1. Image and text areas need to be treated differently by a printer. Typically, image areas are halftoned with a repetitive screen, whereas text areas are not halftoned. The reason for this is that it is desirable for text to be printed with sharp edges.
2. Due to the above mentioned dichotomy in text and image areas, a composite document containing both text and images needs to be segmented into regions containing only text and only images. This segmentation process needs to be done accurately.
3. If a halftoned image prepared for one printer is printed on a second printer, there is a possibility of introducing Moire artifacts (interference fringes), which is a well known phenomenon. This shows up as an undesirable print quality problem.
In accordance with the method of the present invention, the first processing step is to segment a composite document into image and text areas. The text areas are left alone, to be combined at a later stage. The image areas are analyzed to determine their periodic screen frequency, and a smoothing filter is dynamically designed to eliminate the appearance of the screen (i.e. perform descreening). The descreened image is then re-halftoned while taking into consideration the characteristics of the second printer.
There are several potential uses for the method of the present invention:
1. An original halftone prepared for one printer can be printed on another printer without loss of quality and the introduction of artifacts.
2. This technique can also be used to perform image enhancement tasks. For instance, if the original halftoned image had poor contrast, we re-create an intermediate gray level representation, enhance the contrast, and then re-halftone the enhanced image. We can also add some random noise to improve the appearance of texture in the textured areas of the image.